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Monoallelic expression within a gene family is found in pathogens exhibiting antigenic variation and in mammalian olfactory neurons. Trypanosoma brucei, a lethal parasite living in the human bloodstream, expresses variant surface glycoprotein (VSG) from 1 of 15 bloodstream expression sites (BESs) by virtue of a multifunctional RNA polymerase I. The active BES is transcribed in an extranucleolar compartment termed the expression site body (ESB), whereas silent BESs, located elsewhere within the nucleus, are repressed epigenetically. The regulatory mechanisms, however, are poorly understood. Here we show that two essential subunits of the basal class I transcription factor A (CITFA) predominantly occupied the promoter of the active BES relative to that of a silent BES, a phenotype that was maintained after switching BESs in situ. In these experiments, high promoter occupancy of CITFA was coupled to high levels of both promoter-proximal RNA abundance and RNA polymerase I occupancy. Accordingly, fluorescently tagged CITFA-7 was concentrated in the nucleolus and the ESB. Because a ChIP-seq analysis found that along the entire BES, CITFA-7 is specifically enriched only at the promoter, our data strongly indicate that monoallelic BES transcription is activated by a mechanism that functions at the level of transcription initiation.
The ITS2 Database
(2012)
The internal transcribed spacer 2 (ITS2) has been used as a phylogenetic marker for more than two decades. As ITS2 research mainly focused on the very variable ITS2 sequence, it confined this marker to low-level phylogenetics only. However, the combination of the ITS2 sequence and its highly conserved secondary structure improves the phylogenetic resolution1 and allows phylogenetic inference at multiple taxonomic ranks, including species delimitation.
The ITS2 Database presents an exhaustive dataset of internal transcribed spacer 2 sequences from NCBI GenBank accurately reannotated. Following an annotation by profile Hidden Markov Models (HMMs), the secondary structure of each sequence is predicted. First, it is tested whether a minimum energy based fold (direct fold) results in a correct, four helix conformation. If this is not the case, the structure is predicted by homology modeling. In homology modeling, an already known secondary structure is transferred to another ITS2 sequence, whose secondary structure was not able to fold correctly in a direct fold.
The ITS2 Database is not only a database for storage and retrieval of ITS2 sequence-structures. It also provides several tools to process your own ITS2 sequences, including annotation, structural prediction, motif detection and BLAST search on the combined sequence-structure information. Moreover, it integrates trimmed versions of 4SALE and ProfDistS for multiple sequence-structure alignment calculation and Neighbor Joining tree reconstruction. Together they form a coherent analysis pipeline from an initial set of sequences to a phylogeny based on sequence and secondary structure.
In a nutshell, this workbench simplifies first phylogenetic analyses to only a few mouse-clicks, while additionally providing tools and data for comprehensive large-scale analyses.
During the past years, the internal transcribed spacer 2 (ITS2) was established as a commonly used molecular phylogenetic marker for the eukaryotes. Its fast evolving sequence is predestinated for the use in low-level phylogenetics. However, the ITS2 also consists of a very conserved secondary structure. This enables the discrimination between more distantly related species. The combination of both in a sequence-structure based analysis increases the resolution of the marker and enables even more robust tree reconstructions on a broader taxonomic range. But, performing such an analysis required the application of different programs and databases making the use of the ITS2 non trivial for the typical biologist. To overcome this hindrance, I have developed the ITS2 Workbench, a completely web-based tool for automated phylogenetic sequence-structure analyses using the ITS2 (http://its2.bioapps.biozentrum.uni-wuerzburg.de). The development started with an optimization of length modelling topologies for Hidden Markov Models (HMMs), which were successfully applied on a secondary structure prediction model of the ITS2 marker. Here, structure is predicted by considering the sequences' composition in combination with the length distribution of different helical regions. Next, I integrated HMMs into the sequence-structure generation process for the delineation of the ITS2 within a given sequence. This re-implemented pipeline could more than double the number of structure predictions and reduce the runtime to a few days. Together with further optimizations of the homology modelling process I can now exhaustively predict secondary structures in several iterations. These modifications currently provide 380,000 annotated sequences including 288,000 structure predictions. To include these structures in the calculation of alignments and phylogenetic trees, I developed the R-package "treeforge". It generates sequence-structure alignments on up to four different coding alphabets. For the first time also structural bonds were considered in alignments, which required the estimation of new scoring matrices. Now, the reconstruction of Maximum Parsimony, Maximum Likelihood as well as Neighbour Joining trees on all four alphabets requires just a few lines of code. The package was used to resolve the controversial chlorophyceaen dataset and could be integrated into future versions of the ITS2 workbench. The platform is based on a modern, feature-rich Web 2.0 user interface equipped with the latest AJAX and Web-service technologies. It performs HMM-based sequence annotation, structure prediction by energy minimization or homology modelling, alignment calculation and tree reconstruction on a flexible data pool that repeats calculations according to data changes. Further, it provides sequence motif detection to control annotation and structure prediction and a sequence-structure based BLAST search, which facilitates the taxon sampling process. All features and the usage of the ITS2 workbench are explained in a video tutorial. However, the workbench bears some limitations regarding the size of datasets. This is caused mainly due to the immense computational power needed for such extensive calculations. To demonstrate the validity of the approach also for large-scale analyses, a fully automated reconstruction of the Chlorophyta (Green Algal) Tree of Life was performed. The successful application of the marker even on large datasets underlines the capabilities of ITS2 sequence-structure analysis and suggests its utilization on further datasets. The ITS2 workbench provides an excellent starting point for such endeavours.
Marine sponge–associated actinomycetes are considered as promising sources for the discovery of novel biologically active compounds. In the present study, a total of 64 actinomycetes were isolated from 12 different marine sponge species that had been collected offshore the islands of Milos and Crete, Greece, eastern Mediterranean. The isolates were affiliated to 23 genera representing 8 different suborders based on nearly full length 16S rRNA gene sequencing. Four putatively novel species belonging to genera Geodermatophilus, Microlunatus, Rhodococcus and Actinomycetospora were identified based on a 16S rRNA gene sequence similarity of < 98.5% to currently described strains. Eight actinomycete isolates showed bioactivities against Trypanosma brucei brucei TC221 with half maximal inhibitory concentration (IC50) values <20 μg/mL. Thirty four isolates from the Milos collection and 12 isolates from the Crete collection were subjected to metabolomic analysis using high resolution LC-MS and NMR for dereplication purposes. Two isolates belonging to the genera Streptomyces (SBT348) and Micromonospora (SBT687) were prioritized based on their distinct chemistry profiles as well as their anti-trypanosomal activities. These findings demonstrated the feasibility and efficacy of utilizing metabolomics tools to prioritize chemically unique strains from microorganism collections and further highlight sponges as rich source for novel and bioactive actinomycetes.